scholarly journals The Effects of Epigallocatechin Gallate (EGCG) on Pulmonary Fibroblasts of Idiopathic Pulmonary Fibrosis (IPF)—A Next-Generation Sequencing and Bioinformatic Approach

2019 ◽  
Vol 20 (8) ◽  
pp. 1958 ◽  
Author(s):  
Ming-Ju Tsai ◽  
Wei-An Chang ◽  
Ssu-Hui Liao ◽  
Kuo-Feng Chang ◽  
Chau-Chyun Sheu ◽  
...  
Keyword(s):  
Gene Expression ◽  
Next Generation Sequencing ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Epigallocatechin Gallate ◽  
Differentially Expressed ◽  
Pulmonary Fibroblasts ◽  
Generation Sequencing

Idiopathic pulmonary fibrosis (IPF) is a disabling and lethal chronic progressive pulmonary disease. Epigallocatechin gallate (EGCG) is a polyphenol, which is the major biological component of green tea. The anti-oxidative, anti-inflammatory, and anti-fibrotic effects of EGCG have been shown in some studies, whereas its effects in altering gene expression in pulmonary fibroblasts have not been systematically investigated. This study aimed to explore the effect of EGCG on gene expression profiles in fibroblasts of IPF. The pulmonary fibroblasts from an IPF patient were treated with either EGCG or water, and the expression profiles of mRNAs and microRNAs were determined by next-generation sequencing (NGS) and analyzed with the bioinformatics approach. A total of 61 differentially expressed genes and 56 differentially expressed microRNAs were found in EGCG-treated IPF fibroblasts. Gene ontology analyses revealed that the differentially expressed genes were mainly involved in the biosynthetic and metabolic processes of cholesterol. In addition, five potential altered microRNA–mRNA interactions were found, including hsa-miR-939-5p–PLXNA4, hsa-miR-3918–CTIF, hsa-miR-4768-5p–PDE5A, hsa-miR-1273g-3p–VPS53, and hsa-miR-1972–PCSK9. In summary, differentially expressed genes and microRNAs in response to EGCG treatment in IPF fibroblasts were identified in the current study. Our findings provide a scientific basis to evaluate the potential benefits of EGCG in IPF treatment, and warrant future studies to understand the role of molecular pathways underlying cholesterol homeostasis in the pathogenesis of IPF.

scholarly journals Identification of Differentially Expressed Genes Triggered by Aberrant Methylation in Idiopathic Pulmonary Fibrosis Using Integrated Bioinformatic Analysis

2020 ◽  
Author(s):  
Shuaijun Chen ◽  
Jun Zhang ◽  
Wanli Ma ◽  
Hong Ye
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Epigenetic Mechanism ◽  
Integrated Analysis ◽  
Aberrant Methylation ◽  
Mrna Levels

Abstract BackgroundIdiopathic pulmonary fibrosis (IPF) is a relentlessly progressive and fatal fibrotic lung disease all over the world, and specific pathogenesis is still not well understood. DNA methylation is an essential epigenetic mechanism, which likely contributes to the progress of IPF. The purpose of this study is to identify aberrantly methylated differentially expressed genes (DEGs) in IPF and to explore the underlying mechanisms of IPF by using integrated bioinformatics analysis.MethodGene expression profiles and gene methylation profile were downloaded and analyzed to identify the aberrantly methylated‐differentially expressed genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Search Tool for the Retrieval of Interacting Genes Database (STRING) and Gene set enrichment analysis (GSEA) were used to evaluate function of DEGs. RT-PCR was used to verify the mRNA levels of DEGs in mice with pulmonary fibrosis.ResultsBy analyzing the differentially expressed genes of the three IPF expression profiles, and taking the intersection, we got 143 co-upregulated genes and 104 co-downregulated genes; GO and KEGG pathway analysis of the DEGs suggested these genes involved in the extracellular matrix organization, multicellular organismal homeostasis. Combining the sequencing data of two IPF methylation chips, we have identified genes that may be regulated by methylation in IPF. Finally, we obtained the mRNA expression of DEGs using a mouse model of pulmonary fibrosis.ConclusionThrough integrated analysis and experimental verification, we found a series of biomarkers which were regulated by methylation should be potential therapeutic targets for IPF.

scholarly journals Gene Expression Changes Associated with Nintedanib Treatment in Idiopathic Pulmonary Fibrosis Fibroblasts: A Next-Generation Sequencing and Bioinformatics Study

2019 ◽  
Vol 8 (3) ◽  
pp. 308 ◽  
Author(s):  
Chau-Chyun Sheu ◽  
Wei-An Chang ◽  
Ming-Ju Tsai ◽  
Ssu-Hui Liao ◽  
Inn-Wen Chong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Next Generation Sequencing ◽  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Protein Interactions ◽  
Next Generation ◽  
Protein Protein Interactions ◽  
Bioinformatics Study ◽  
Generation Sequencing

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive, and fatal interstitial lung disease. Therapeutic options for IPF remain limited. Nintedanib, a tyrosine kinase inhibitor approved for IPF treatment, is known to inhibit fibroblasts proliferation, migration and transformation to myofibroblasts. However, how nintedanib changes gene regulations in IPF has never been systematically investigated. We conducted a next-generation sequencing and bioinformatics study to evaluate the changes of mRNA and miRNA profiles in IPF fibroblasts treated with 2 µM and 4 µM nintedanib, compared to those without treatment. We identified 157 upregulated and 151 downregulated genes and used STRING and DAVID databases for analysis of protein–protein interactions, biological pathways, and molecular functions. We found strong protein–protein interactions within these dysregulated genes, mostly involved in the pathways of cell cycle and mitotic cell cycle. We also discovered 13 potential miRNA–mRNA interactions associated with nintedanib treatment. After validation using miRDB, TargetScan, and RT-qPCR, we identified 4 downregulated genes (DDX11, E2F1, NPTX1, and PLXNA4) which might be repressed by the upregulated hsa-miR-486-3p. According to the proposed functions of DDX11, E2F1, and PLXNA4 reported in previous studies, these gene expression changes together might contribute to decreased proliferation of fibroblasts and decreased angiogenesis in the microenvironment of IPF. Our findings need further studies to confirm.

scholarly journals Identification of differentially expressed genes triggered by aberrant methylation in idiopathic pulmonary fibrosis using integrated bioinformatic analysis

2021 ◽  
Author(s):  
Shuaijun Chen ◽  
Jun Zhang ◽  
Wanli Ma ◽  
Hong Ye
Keyword(s):  
Idiopathic Pulmonary Fibrosis ◽  
Pulmonary Fibrosis ◽  
Differentially Expressed Genes ◽  
Expression Profiles ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
Epigenetic Mechanism ◽  
Integrated Analysis ◽  
Aberrant Methylation ◽  
Mrna Levels

Abstract Background Idiopathic pulmonary fibrosis (IPF) is a relentlessly progressive and fatal fibrotic lung disease all over the world, and specific pathogenesis is still not well understood. DNA methylation is an essential epigenetic mechanism, which likely contributes to the progress of IPF. The purpose of this study is to identify aberrantly methylated differentially expressed genes (DEGs) in IPF and to explore the underlying mechanisms of IPF by using integrated bioinformatics analysis.Methods Gene expression profiles and gene methylation profiles were downloaded and analyzed to identify the aberrantly methylated‐differentially expressed genes. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Search Tool for the Retrieval of Interacting Genes Database (STRING), and Gene set enrichment analysis (GSEA) were used to evaluate the function of DEGs. RT-PCR was used to verify the mRNA levels of DEGs in mice with pulmonary fibrosis.Results By analyzing the differentially expressed genes of the three IPF expression profiles, and taking the intersection, we got 143 co-upregulated genes and 104 co-downregulated genes; GO and KEGG pathway analysis of the DEGs suggested these genes involved in the extracellular matrix organization, multicellular organismal homeostasis. Combining the sequencing data of two IPF methylation chips, we have identified genes that may be regulated by methylation in IPF. Finally, we obtained the mRNA expression of DEGs using a mouse model of pulmonary fibrosis.Conclusions Through integrated analysis and experimental verification, we found a series of biomarkers that were regulated by methylation should be potential therapeutic targets for IPF.

scholarly journals HIV-1 Infection Transcriptomics: Meta-Analysis of CD4+ T Cells Gene Expression Profiles

Viruses ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 244 ◽  
Author(s):  
Antonio Victor Campos Coelho ◽  
Rossella Gratton ◽  
João Paulo Britto de Melo ◽  
José Leandro Andrade-Santos ◽  
Rafael Lima Guimarães ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cells ◽  
Differentially Expressed Genes ◽  
Cd4 T Cells ◽  
Expression Profiles ◽  
Meta Analysis ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Infected Cells ◽  
Hiv 1

HIV-1 infection elicits a complex dynamic of the expression various host genes. High throughput sequencing added an expressive amount of information regarding HIV-1 infections and pathogenesis. RNA sequencing (RNA-Seq) is currently the tool of choice to investigate gene expression in a several range of experimental setting. This study aims at performing a meta-analysis of RNA-Seq expression profiles in samples of HIV-1 infected CD4+ T cells compared to uninfected cells to assess consistently differentially expressed genes in the context of HIV-1 infection. We selected two studies (22 samples: 15 experimentally infected and 7 mock-infected). We found 208 differentially expressed genes in infected cells when compared to uninfected/mock-infected cells. This result had moderate overlap when compared to previous studies of HIV-1 infection transcriptomics, but we identified 64 genes already known to interact with HIV-1 according to the HIV-1 Human Interaction Database. A gene ontology (GO) analysis revealed enrichment of several pathways involved in immune response, cell adhesion, cell migration, inflammation, apoptosis, Wnt, Notch and ERK/MAPK signaling.

scholarly journals Uncontrolled Diabetes Mellitus Has No Major Influence on the Platelet Transcriptome

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Thomas G. Nührenberg ◽  
Marco Cederqvist ◽  
Federico Marini ◽  
Christian Stratz ◽  
Björn A. Grüning ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Next Generation Sequencing ◽  
Platelet Reactivity ◽  
Platelet Rich Plasma ◽  
Expression Profiles ◽  
Bioinformatic Analysis ◽  
Differentially Expressed ◽  
Major Influence ◽  
Next Generation ◽  
Generation Sequencing

Background. Diabetes mellitus (DM) has been associated with increased platelet reactivity as well as increased levels of platelet RNAs in plasma. Here, we sought to evaluate whether the platelet transcriptome is altered in the presence of uncontrolled DM. Methods. Next-generation sequencing (NGS) was performed on platelet RNA for 5 patients with uncontrolled DM (HbA1c 9.0%) and 5 control patients (HbA1c 5.5%) with otherwise similar clinical characteristics. RNA was isolated from leucocyte-depleted platelet-rich plasma. Libraries of platelet RNAs were created separately for long RNAs after ribosomal depletion and for small RNAs from total RNA, followed by next-generation sequencing. Results. Platelets in both groups demonstrated RNA expression profiles characterized by absence of leukocyte-specific transcripts, high expression of well-known platelet transcripts, and in total 6,343 consistently detectable transcripts. Extensive statistical bioinformatic analysis yielded 12 genes with consistently differential expression at a lenient FDR < 0.1, thereof 8 protein-coding genes and 2 genes with known expression in platelets (MACF1 and ITGB3BP). Three of the four differentially expressed noncoding genes were YRNAs (RNY1, RNY3, and RNY4) which were all downregulated in DM. 23 miRNAs were differentially expressed between the two groups. Of the 13 miRNAs with decreased expression in the diabetic group, 8 belonged to the DLK1–DIO3 gene region on chromosome 14q32.2. Conclusions. In this study, uncontrolled DM had a remote impact on different components of the platelet transcriptome. Increased expression of MACF1, together with supporting predicted mRNA-miRNA interactions as well as reduced expression of RNYs in platelets, may reflect subclinical platelet activation in uncontrolled DM.

scholarly journals Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

2021 ◽  
Author(s):  
Li Guoquan ◽  
Du Junwei ◽  
He Qi ◽  
Fu Xinghao ◽  
Ji Feihong ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Inflammatory Responses ◽  
Expression Profiles ◽  
Treatment Options ◽  
Enrichment Analysis ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Chronic Lymphocytic Thyroiditis ◽  
Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

scholarly journals Insight into Molecular Profile Changes after Skeletal Muscle Contusion Using Microarray and Bioinformatics Analyses

2020 ◽  
Author(s):  
Na Li ◽  
Ru-feng Bai ◽  
Chun Li ◽  
Li-hong Dang ◽  
Qiu-xiang Du ◽  
...  
Keyword(s):  
Gene Expression ◽  
Network Analysis ◽  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Expression Profiles ◽  
Healing Process ◽  
Differentially Expressed ◽  
Molecular Profile ◽  
Wound Age ◽  
Functional Modules

Abstract Background: Muscle trauma frequently occurs in daily life. However, the molecular mechanisms of muscle healing, which partly depend on the extent of the damage, are not well understood. This study aimed to investigate gene expression profiles following mild and severe muscle contusion, and to provide more information about the molecular mechanisms underlying the repair process.Methods: A total of 33 rats were divided randomly into control (n = 3), mild contusion (n = 15), and severe contusion (n = 15) groups; the contusion groups were further divided into five subgroups (1, 3, 24, 48, and 168 h post-injury; n = 3 per subgroup). Then full genome microarray of RNA isolated from muscle tissue was performed to access the gene expression changes during healing process.Results: A total of 2,844 and 2,298 differentially expressed genes were identified in the mild and severe contusion groups, respectively. The analysis of the overlapping differentially expressed genes showed that there are common mechanisms of transcriptomic repair of mild and severe contusion within 48 h post-contusion. This was supported by the results of principal component analysis, hierarchical clustering, and weighted gene co‐expression network analysis of the 1,620 coexpressed genes in mildly and severely contused muscle. From these analyses, we discovered that the gene profiles in functional modules and temporal clusters were similar between the mild and severe contusion groups; moreover, the genes showed time-dependent patterns of expression, which allowed us to identify useful markers of wound age. We then performed an analysis of the functions of genes (including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway annotation, and protein–protein interaction network analysis) in the functional modules and temporal clusters, and the hub genes in each module–cluster pair were identified. Interestingly, we found that genes downregulated within 24−48 h of the healing process were largely associated with metabolic processes, especially oxidative phosphorylation of reduced nicotinamide adenine dinucleotide phosphate, which has been rarely reported. Conclusions: These results improve our understanding of the molecular mechanisms underlying muscle repair, and provide a basis for further studies of wound age estimation.

scholarly journals Gene Expression Profiles of Papillary Thyroid Microcarcinoma

2017 ◽  
Vol 102 (1-2) ◽  
pp. 39-46 ◽  
Author(s):  
Woo Young Kim ◽  
Jae Bok Lee ◽  
Seung Pil Jung ◽  
Hoon Yub Kim ◽  
Sang Uk Woo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profile ◽  
Differentially Expressed Genes ◽  
Expression Profile ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Papillary Thyroid Microcarcinoma ◽  
Papillary Thyroid ◽  
Normal Thyroid ◽  
Thyroid Microcarcinoma

The objective was to identify gene expression profile of papillary thyroid microcarcinoma. To help improve diagnosis of papillary thyroid microcarcinoma, we performed gene expression profiling and compared it to pair normal thyroid tissues. We performed microarray analysis with 6 papillary thyroid microcarcinoma and 6 pair normal thyroid tissues. Differentially expressed genes were selected using paired t test, linear models for microarray data, and significance analysis of microarrays. Real-time quantitative reverse transcription–polymerase chain reaction was used to validate the representative 10 genes (MET, TIMP1, QPCT, PROS1, LRP4, SDC4, CITED1, DPP4, LRRK2, RUNX2). We identified 91 differentially expressed genes (84 upregulated and 7 downregulated) in the gene expression profile and validated 10 genes of the profile. We identified a significant genetic difference between papillary thyroid microcarcinoma and normal tissue by 10 upregulated genes greater than 2-fold (P &lt; 0.05).

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